Do you want beneficial technologies being shaped by your ideas? Whether in the areas of mobility solutions, consumer goods, industrial technology or energy and building technology - with us, you will have the chance to improve quality of life all across the globe. Welcome to Bosch.
The Robert Bosch GmbH is looking forward to your application!
Employment type: Limited
Working hours: Full-Time
Joblocation: Renningen
Aufgaben
- As a PhD candidate with us, you will dive deep into the world of agentic AI systems and contribute significantly to the development of intelligent solutions for real-world challenges, combining cutting-edge research with direct industrial impact.
- You will work on developing the next generation of AI systems for industrial applications and apply your expertise in practical projects.
- Adapting foundation models efficiently and orchestrating multi-agent systems will be at the core of your work.
- You will integrate knowledge graphs and retrieval-augmented generation (RAG) into innovative AI architectures.
- A key part of your role involves researching and applying reinforcement learning–based training approaches for intelligent agents.
- Last but not least, you will continuously validate your research results using real engineering use cases at Bosch, contributing directly to the advancement of modern enterprise processes.
Profil
- Education: excellent Master's degree in Computer Science, Artificial Intelligence, Mathematics, or a comparable field
- Experience and Knowledge:
- strong knowledge of large language models (LLMs), foundation models, and deep learning, combined with hands-on experience in fine-tuning (e.g. SFT, RLHF/RLAIF) or parameter-efficient adaptation methods such as LoRA or adapters
- experience with retrieval-augmented generation (RAG), including dense retrieval, reranking, and advanced architectures, as well as the integration of knowledge graphs, ontologies, or other knowledge engineering approaches (ideally with SPARQL, Cypher, or KG embeddings)
- familiarity with multi-agent systems or agentic frameworks (e.g. LangGraph, AutoGen, CrewAI), including aspects of agent safety, controllability, and human-in-the-loop approaches
- strong programming skills in Python and experience with machine learning frameworks, ideally complemented by knowledge of reinforcement learning (e.g. RL, RLHF, policy optimization)
- experience in evaluating agentic systems using relevant frameworks or benchmarks, ideally complemented by contributions to scientific publications
- Personality and Working Practice: you combine analytical thinking with a self-driven, structured approach, delivering results and taking ownership of your tasks; in international, collaborative environments, you stand out through strong communication and presentation skills
- Languages: fluent in English
Wir bieten
- Work-life balance: Flexible working in terms of time, place and working model.
- Health & Sport: Wide range of health and sports activities.
- Childcare: Intermediary service for childcare services.
- Employee discounts: Discounts for employees.
- Room for creativity: Space for creative work.
- In-house social counseling and care services: Social counselling and intermediary service for care services.
The recruitment contact or superior will be happy to provide information about the individual benefit plan.
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